Evolving Roles in Salesforce: How to Get Your Team AI Ready

You’d be hard-pressed to find a business that doesn’t want to leverage AI. But to effectively do so, you need to achieve a state of AI readiness that ensures you have the foundation to make AI truly work for you. 

A crucial part of AI is understanding the interplay between historical and real-time Salesforce data. Historical data provides a valuable retrospective view, offering insights into long-term trends, customer lifecycle patterns, and shifts in market dynamics. This data is indispensable for identifying enduring patterns and making predictions about future behaviors and preferences.

Conversely, real-time data offers an immediate snapshot of customer interactions, market movements, and operational dynamics. It’s the pulse of current business activities, providing a live feed of what’s happening at any given moment. Essential for agile decision-making, it allows businesses to respond swiftly to emerging trends, customer needs, and sudden market shifts.  

Integrating both historical and real-time data is critical for creating a comprehensive 360 degree view of the customer. Together, they provide the full dataset to properly feed AI to create the balanced perspective businesses need to make holistic, informed decisions using all their data.

In this article, we will cover how Salesforce roles are evolving with the explosion of AI and provide a checklist to ensure your team is primed to leverage AI for strategic insights and success.

How Roles are Evolving in Salesforce Teams

With no trough of disillusionment in sight for AI, Salesforce Admins, Developers, and business leaders need to start steering their teams toward AI readiness in order to stay competitive. This AI journey is about more than just handling vast amounts of data; it’s about actually weaving this data into the very fabric of business intelligence and strategy. 

Business leaders finally have the ability to ask questions about their data and can rely on it to provide comprehensive answers in a timely manner. But to do this effectively they need admins and developers to master the arts of efficient data management and data extraction – laying a strong foundation for an architecture that effectively supports the demand on AI.

Salesforce Admins

With the growing use of AI tools and the necessity to consume customer data faster, admins will be heavily relied on for data management as the foundation of AI, especially around:

• Collecting and processing data securely into Salesforce.
• Managing and organizing datasets.
• Ensuring data quality and governance.

The role admins play is critical in building a resilient data foundation that feeds advanced AI solutions, which contributes significantly to assisting business leaders in making well-informed decisions.

Salesforce Developers

Developers will be tasked with redesigning structures and integrating Einstein AI features that enable their organization to harness the power of AI faster. They will be expected to engage in data preparation and management as well to ensure high-quality datasets that are suitable for AI processing inside and outside of Salesforce.

Developers will serve as the bridge that connects the admin’s data management efforts with AI to create integrations, dashboards, models, and more to help business leaders make better data-driven decisions.

Business Leaders

For business leaders, the journey toward AI readiness is a strategic endeavor that requires collaboration amongst your Salesforce team.

Working with admins and developers is essential to ensure you have adequate datasets and data flows set up for consumption and analysis while supporting compliance regulations. That way you can be sure that the data you are using to make decisions is accurate.

AI Readiness Checklist

It’s clear that each role within a Salesforce team plays a pivotal part in harnessing the power of AI inside and outside of Salesforce. Use this checklist as a roadmap, guiding your team on what they should focus on and helping to align your efforts with the goal of achieving AI readiness.

1. Understanding AI’s Role: Let’s start with the basics: does everyone on your team understand how AI fits into your Salesforce environment? Remember, knowing AI’s purpose is key to managing and extracting data effectively.
2. Data Architecture Check: Take a look at your data setup. Is it ready to embrace AI technologies in Salesforce, as well as outside of it? It’s crucial to have a data architecture that supports AI, insights, and reporting – especially if you want to leverage external tools.
3. Evaluating Data Extraction: How quick and efficient is your data extraction process currently? You must be able to streamline and automate extraction in order to make your historical and live data readily available for AI. 
4. Exploring AI Integration: Has your organization started integrating AI into your Salesforce operations? Make sure to outline the steps to bring AI-driven solutions into your workflows.
5. Maximizing Salesforce AI Features: Are you making the most of the data and insights tools Salesforce offers for data? With tools like Data Cloud and CRM Analytics, organizations can easily pipe and consume near real-time Salesforce data. 
6. Navigating AI Challenges: What hurdles are you facing in adopting AI? Identifying these challenges will help your organization find smooth ways to integrate data needed to make better predictions.
7. Ensuring Data Quality: How robust are your data quality and governance measures? Clean data is an essential part of data management, especially when it comes to using it to formulate better predictions of outcomes. 
8. Future-Proofing Your Organization for AI: Finally, is the team keeping up with the latest AI developments? Whether you use Salesforce features or other popular tools, such as AWS Sagemaker or Google BigQuery, continuous learning and adaptation are crucial to effectively navigate the emerging AI landscape.

How Salesforce and GRAX Can Help 

By using GRAX with Salesforce, your team can unleash the power of your Salesforce datasets to uncover patterns from historical to near real-time data. This combined solution enables data scientists and AI models to work with a rich, multifaceted dataset, ensuring nuanced and accurate predictions. It’s about creating a dynamic, data-driven ecosystem that is constantly fed by both past experiences and present interactions.

With GRAX, you can turn your data into a fountain of insights, leading your organization toward a future where every decision is informed, every strategy is data-driven, and every outcome is a step toward innovation and growth. GRAX not only fortifies your data strategy but also ensures compliance and data integrity, making it a vital component of your AI readiness journey.

Watch our demo to learn more about how GRAX can help your team easily capture, replicate, and pipe every historical version of Salesforce data with a couple of clicks.